Working with diligence
Pasting customer data into an AI tool, or sharing a generated document without saying so, can cost you the trust of a customer or a team. This lesson helps you decide what to share with the tool, adjust its privacy settings and stay accountable for everything you publish with AI's help.
Lesson objective
By the end of this lesson, you will be able to decide which data to share with an AI tool, adjust its privacy settings, and apply a diligence checklist (data, checking, transparency, accountability) before circulating a deliverable produced with AI.
Topics covered
- AI data privacy
- responsible AI use
- AI transparency
- personal data
Where it fits
Set up an assistant, work with diligence
How do you stop starting from scratch, hand more work to AI and stay accountable for the result?
Lessons in this module
- Stop repeating yourself with standing instructions and projects
- Building a dedicated assistant, then handing tasks to an agent
- Working with diligence (this lesson)
What you will learn in this module
This lesson is part of the course Prompting for Product Managers: delegate, describe, verify
- Configure standing instructions and a dedicated assistant for a recurring task, test it on real cases, and decide when to move to an agent.
- Apply diligence rules (shared data, transparency, accountability) before using or circulating work produced with AI.
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